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Linear refractive index and density prediction of transparent B2O3-CaO-Li2O glasses reinforced with Sb2O3 utilizing machine learning techniques

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Abstract

In the present study, for the first time the machine learning (ML) based refractive index (n) approach is established depends on the density (ρ) parameter of glasses for a dataset of 2000 oxide glasses to predict refractive index of B2O3-CaO-Li2O-Sb2O3 glasses. Density of the investigated glasses varied from 2.56 to 2.97 gm/cm3. The corresponding refractive index was changed from 2.540 to 2.405. The refractive index prediction based on density parameter derived from the density of glasses and constant ‘K’. For all M-L techniques including gradient descent (GD), artificial neural network (ANN), and random forest regression (RFR), the density factor is used as an independent variable and the experimental refractive index as a dependent variable. The data set of 10,000 oxide glass samples was employed to forecast density using a variety of machine learning approaches. In comparison to other models, the Random forest regression (RFR) model fitted the glass data with the highest R2 value of 0.949 for refractive index prediction and 0.925 for density prediction. For both the prediction of density and refractive index, the R2 is controlled to 0.932 and 0.9223, respectively. The highest R2 values for refractive index and density prediction were gained when the tanh activation function was used in an artificial neural network (ANN) with varied activation functions.

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Acknowledgements

The authors express their gratitude to Princess Nourah bint Abdulrahman, University Researchers Supporting Project (Grant No. PNURSP2024R28), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia. The authors extend their appreciation to the Deanship of Scientific Research at Northern Border University, Arar, KSA for funding this research work through the project number “NBU-FFR-2023-0163”.

Author information

Authors and Affiliations

  1. Department of Physics, College of Science, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia

    Hanan Al-Ghamdi & Norah A. M. Alsaif

  2. Department of Physics, Muffakham Jah College of Engineering and Technology, Hyderabad, 500034, Telangana State, India

    Shaik Kareem Ahmmad

  3. Department of Computer Science and Artificial Intelligence, Muffakham Jah College of Engineering and Technology, Hyderabad, 500034, Telangana State, India

    M. M. Ahmed

  4. Physics and Mathematical Engineering Department, Faculty of Electronic Engineering, Menoufia University, Menouf, 32952, Egypt

    M. S. Shams

  5. Department of Basic and Applied Science, Collage of Engineering and Technology, Arab Academy of Science, Technology and Maritime Transport, Smart Village, Giza, Egypt

    M. S. Shams & Adel M. El-Refaey

  6. Spectroscopy Department, National Research Centre, 33 Elbehouth St., Dokki, Cairo, 12622, Egypt

    A. M. Abdelghany

  7. Department of Electrical Engineering, College of Engineering, Northern Border University, 1321, Arar, Saudi Arabia

    Shaaban M. Shaaban

  8. Department of Physics, Faculty of Science, Menoufia University, Shebin El-Koom, 32511, Egypt

    Y. S. Rammah

  9. Basic Engineering Science Department, Faculty of Engineering, Menoufia University, Shebin El-Koom, 32511, Egypt

    R. A. Elsad

Authors
  1. Hanan Al-Ghamdi
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  2. Norah A. M. Alsaif
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  3. Shaik Kareem Ahmmad
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  4. M. M. Ahmed
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  5. M. S. Shams
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  6. Adel M. El-Refaey
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  7. A. M. Abdelghany
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  8. Shaaban M. Shaaban
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  9. Y. S. Rammah
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  10. R. A. Elsad
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Contributions

Norah A.M. Alsaif: Conceptualization, Methodology, Software, Validation, Investigation, Data Curation, Writing-Review and Editing, Visualization.

Shaik Kareem Ahmmad: Conceptualization, Methodology, Software, Validation, Investigation, Data Curation, Writing-Review and Editing, Visualization, Supervision.

Hanan Al-Ghamdi: Conceptualization, Methodology, Software, Validation, Investigation, Data Curation, Writing-Review and Editing, Visualization.

M.M. Ahmed: Conceptualization, Methodology, Software, Validation, Investigation, Data Curation, Writing-Review and Editing, Visualization.

M.S. Shams: Conceptualization, Investigation, Data Curation, Writing-Review and Editing, Visualization.

Adel M. El-Refaey: Conceptualization, Investigation, Data Curation, Writing-Review and Editing, Visualization.

A.M. Abdelghany: Conceptualization, Methodology, Software, Validation, Investigation, Data Curation, Writing-Review and Editing, Visualization.

Y.S. Rammah: Conceptualization, Methodology, Software, Validation, Investigation, Data Curation, Writing-Review and Editing, Visualization, Supervision.

R.A. Elsad: Conceptualization, Methodology, Software, Validation, Investigation, Data Curation, Writing-Review and Editing, Visualization.

Corresponding author

Correspondence to R. A. Elsad.

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Al-Ghamdi, H., Alsaif, N.A.M., Ahmmad, S.K. et al. Linear refractive index and density prediction of transparent B2O3-CaO-Li2O glasses reinforced with Sb2O3 utilizing machine learning techniques. J Aust Ceram Soc (2024). https://doi.org/10.1007/s41779-024-01006-w

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